You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Describe the bug
Flowise ORM fails to specify the dimension count for the vector column when creating tables for RAG (Retrieval-Augmented Generation) in a PostgreSQL database. This results in an error 'SQL Error [XX000]: ERROR: column does not have dimensions' when trying to create an index on that column.
To Reproduce
Steps to reproduce the behavior:
Go to 'Flowise application'
Navigate to the section where you can manage database tables
Create a new table for RAG with an embedding column
Try to create an index on the embedding column
Encounter the 'SQL Error [XX000]: ERROR: column does not have dimensions' error
Expected behavior
I expected the ORM to automatically specify the vector dimension count for the embedding column, allowing users to create indexes without issues.
Screenshots
Flow
Setup
Installation docker
Flowise Version 1.6.6
OS: Linux
Browser Chrome
Additional context
This issue affects the functionality of storing and retrieving vector data of specific dimensions. A temporary workaround is to manually specify a vector type with the correct dimensions directly in the database, but this bypasses the automated process through the ORM.
The text was updated successfully, but these errors were encountered:
Describe the bug
Flowise ORM fails to specify the dimension count for the vector column when creating tables for RAG (Retrieval-Augmented Generation) in a PostgreSQL database. This results in an error 'SQL Error [XX000]: ERROR: column does not have dimensions' when trying to create an index on that column.
To Reproduce
Steps to reproduce the behavior:
Expected behavior
I expected the ORM to automatically specify the vector dimension count for the embedding column, allowing users to create indexes without issues.
Screenshots
Flow
Setup
Additional context
This issue affects the functionality of storing and retrieving vector data of specific dimensions. A temporary workaround is to manually specify a vector type with the correct dimensions directly in the database, but this bypasses the automated process through the ORM.
The text was updated successfully, but these errors were encountered: